How Biometrics are Impacted by Racial Bias: An Overview
Introduction
Biometrics has become an integral part of our daily lives, from unlocking our smartphones to accessing our bank accounts. Biometric systems use unique physical and behavioral traits to identify and verify a person’s identity. However, recent studies have shown that these systems may be susceptible to racial bias.
The Problem with Racial Bias in Biometrics
Racial bias in biometrics occurs when these systems disproportionately fail to recognize the physical characteristics of certain racial groups. This can lead to false identification and exclusion of individuals who belong to these communities. For example, facial recognition systems have been shown to be up to 100 times more likely to misidentify people of color than white people.
This issue is especially prevalent in law enforcement, where biometric systems are often used to identify suspects. Studies have shown that these systems are more likely to produce false positives for people of color, leading to wrongful arrests and accusations.
How Racial Bias in Biometrics Occurs
Racial bias in biometrics can occur in many ways. One of the main reasons is the lack of diversity in the database used to train these systems. These databases are often biased towards white individuals, making it difficult for the system to accurately recognize people of color.
Another reason is the algorithms used to identify people. These algorithms may be biased towards certain physical features, such as lighter skin or a narrower nose, that are more common in one racial group.
Examples of Racial Bias in Biometrics
One prominent example of racial bias in biometrics is the case of Robert Julian-Borchak Williams, a black man who was wrongfully arrested after facial recognition software identified him as a suspect. The software used by the police department was shown to have higher error rates for people of color, leading to Williams’ unjust arrest.
Another example is the use of biometric systems to screen job applicants. Studies have shown that these systems may be biased towards white applicants, leading to the exclusion of qualified applicants from other racial groups.
Conclusion
Racial bias in biometrics is a serious issue that needs to be addressed. As biometric systems become more prevalent in our daily lives, it is important to ensure that they are fair and unbiased. This can be achieved by increasing the diversity of the databases used to train these systems, improving algorithms to eliminate biases, and implementing policies to ensure that these systems do not disproportionately affect certain groups.
It is crucial to recognize that biometrics is not a perfect science and must be used with caution. As users, we must also be aware of the potential biases in these systems and actively work towards eliminating them. By doing so, we can ensure that biometrics is used as a tool for inclusivity and not as a means of discrimination.
